Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Continuing Care01:25

Continuing Care

1.6K
Continuing care describes the variety of health, personal, and social services provided over a prolonged period. The need for continuing care is increasing because people are living longer. Many people do not have families or others to care for them. Continuing care is mainly for patients who are disabled, functionally dependent, or suffering from a terminal disease. It is available within institutional settings or in homes. Examples include nursing centers or facilities, assisted living,...
1.6K
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

285
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
285
Cancer Survival Analysis01:21

Cancer Survival Analysis

453
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
453
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

196
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
196
Truncation in Survival Analysis01:09

Truncation in Survival Analysis

300
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
300
Actuarial Approach01:20

Actuarial Approach

133
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
133

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Antibiotics in Hospice: Applying the Four-Quadrant Approach to Improve Patient-Centered Care.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America·2026
Same author

Buprenorphine: Changes in legislation and implications for dental care professionals.

Journal of the American Dental Association (1939)·2026
Same author

A Case Report of End-of-Dosage Failure With Buprenorphine Patch.

Journal of pain and symptom management·2026
Same author

Post-Operative Bleed Risks Associated with Perioperative Nonsteroidal Anti-Inflammatory Drugs: A Narrative Review.

Journal of pain & palliative care pharmacotherapy·2025
Same author

Common Antimicrobial Treatment Considerations for Patients Receiving Comfort-Focused Care: What the Hospice Provider Should Know.

Journal of palliative medicine·2025
Same author

Determinants of Antibiotic Prescription in Outpatient Hospice: A Regional Observational Study.

The American journal of hospice & palliative care·2025
Same journal

Relationships Between Advance Care Planning Engagement, Patients' Religious Practices, and Spirituality.

The American journal of hospice & palliative care·2026
Same journal

The Efficacy of Spiritual Care Intervention on Readmissions of Hospitalized Patients Receiving Palliative Care: A Quasi-Experimental Pilot Study Proposal.

The American journal of hospice & palliative care·2026
Same journal

Nurse-Led Advance Care Planning Interventions for Patients with Advanced Cancer: A Systematic Review.

The American journal of hospice & palliative care·2026
Same journal

Self-Reported Cannabis Use and Symptom Burden Among Patients With Cancer Receiving Palliative Care.

The American journal of hospice & palliative care·2026
Same journal

Efficacy of Oxygen Therapy for the Relief of Dyspnea in Palliative Care: A Systematic Review.

The American journal of hospice & palliative care·2026
Same journal

Survival Heterogeneity in U.S. Hospice Patients: A Retrospective Cohort Study.

The American journal of hospice & palliative care·2026
See all related articles

Related Experiment Video

Updated: Sep 10, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.3K

Survival Variations Based on Hospice Qualifying Condition: A Retrospective Review.

Patrick D Crowley1, Leslie R Siegel2,3, Francis X Whalen3,4

  • 1Division of Public Health, Infectious Disease, and Occupational Medicine, Mayo Clinic, Rochester, MN, USA.

The American Journal of Hospice & Palliative Care
|August 26, 2025
PubMed
Summary
This summary is machine-generated.

Hospice patients

Keywords:
elderlyend of lifehospicehospice qualifying conditionsurvival

More Related Videos

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

376
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.6K

Related Experiment Videos

Last Updated: Sep 10, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.3K
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

376
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.6K

Area of Science:

  • Gerontology
  • Palliative Care
  • Biostatistics

Background:

  • Hospice enrollment serves diverse patient conditions.
  • Limited recent data exists on survival duration post-hospice enrollment.
  • Key demographic and diagnostic factors influencing survival are under-examined.

Purpose of the Study:

  • To analyze survival durations after hospice enrollment.
  • To investigate the impact of age, sex, and hospice-qualifying conditions (HQC) on survival.
  • To identify patient subgroups with longer hospice survival.

Main Methods:

  • Utilized existing patient data for analysis.
  • Calculated age at enrollment and recorded sex.
  • Classified patients into nine hospice-qualifying condition categories.
  • Employed Wilcoxon rank-sum tests for survival comparisons.

Main Results:

  • Median survival was 17.36 days; "Infectious" HQC had the shortest median survival (4.69 days), while "Other" had the longest (28.53 days).
  • Women (19.34 days) and older patients (20.51 days) exhibited longer median survival than men (15.37 days) and younger patients (15.03 days).
  • 9.47% of patients survived at least 6 months, with higher rates observed in women (10.99%), older individuals (12.44%), and those with dementia (16.46%).

Conclusions:

  • Survival duration in hospice varies significantly by age, sex, and diagnosis.
  • Findings suggest potential biases in hospice applicability assessments.
  • Understanding these survival differences is vital for patient and family expectations and care planning.